Fuzzy Tsukamoto based Decision Support Model for Purchase Decision in Pharmacy Company

Abstract

The difficulty in determining a number of item purchased is one of essential activities in inventory management. This study scientifically proposes a decision support model to decide how much number of next item purchased by a pharmacy company. The main objective of the developed model is to control a minimum stock at a certain time and condition and support in making the decision on how many items should be purchased at next time. Decision support model considers two independent parameters; lead time and stock. Tsukamoto’s fuzzy system is functioned in this study to avoid blurring parameter values from someone making a decision. Each criterion is divided into three membership functions; with nine fuzzy-rules used. The model also supports changing parameters if parameter values are changed. Based on the results of model test done, the optimized number of item purchased at the Pharmacy Company is able to be proposed practically.